ISE 4120: Quality and Reliability Engineering Homework 3 (Due on Thursday 2/27/2020 at the beginning of the class) Instruction - This assignment should be submitted online in Carmen. Sub- mit your report as one .pdf file and your Python codes for all problems as one .py file separately. Do not compress them into one file. The python code should be separated into different cells (using "#%%" command) for different problems and have a label for each problem. In your report include your python code for each problem along with the output in the order of the problems (no appendix), and a brief description of the results. Failure to follow this instruction will result in a penalty. For Python codes, you may refer to the 'stat infer.py' on Github. Problem 2. (15 pts) The service life of a battery used in a cardiac pacemaker is assumed to be normally distributed. A random sample of ten batteries is subjected to an acceerated life test by running them continuously at an elevated temperature until failure, and the following lifetimes (in hours) are obtained: 25.5, 26.1, 26.8, 23.2, 24.2, 28.4, 25.0, 27.8, 27.3, and 25.7. (a) The manufacturer wants to be certain that the mean battery life exceeds 25 h. What conclusions can be drawn from these data (use a = 0.05)? (b) Construct a 90% two-sided confidence interval on mean life in the accel- erated test. Class, Problem 3 - The \sigma in parts (b) and (c) should be \sigma^2 (i.e. variance and not standard deviation). Also, In the "stat infer.py" file where ever I had the std(data) function (to calculate the standard deviation), you need to replace it with std(data, ddof=1) to get an unbiased estimate of the standard deviation. I just updated the python file on GitHub. ISE 4120: Quality and Reliability Engineering Homework 3 (Due on Thursday 2/27/2020 at the beginning of the class) Instruction - This assignment should be submitted online in Carmen. Sub- mit your report as one .pdf file and your Python codes for all problems as one .py file separately. Do not compress them into one file. The python code should be separated into different cells (using "#%%" command) for different problems and have a label for each problem. In your report include your python code for each problem along with the output in the order of the problems (no appendix), and a brief description of the results. Failure to follow this instruction will result in a penalty. For Python codes, you may refer to the 'stat infer.py' on Github. Problem 2. (15 pts) The service life of a battery used in a cardiac pacemaker is assumed to be normally distributed. A random sample of ten batteries is subjected to an acceerated life test by running them continuously at an elevated temperature until failure, and the following lifetimes (in hours) are obtained: 25.5, 26.1, 26.8, 23.2, 24.2, 28.4, 25.0, 27.8, 27.3, and 25.7. (a) The manufacturer wants to be certain that the mean battery life exceeds 25 h. What conclusions can be drawn from these data (use a = 0.05)? (b) Construct a 90% two-sided confidence interval on mean life in the accel- erated test. Class, Problem 3 - The \sigma in parts (b) and (c) should be \sigma^2 (i.e. variance and not standard deviation). Also, In the "stat infer.py" file where ever I had the std(data) function (to calculate the standard deviation), you need to replace it with std(data, ddof=1) to get an unbiased estimate of the standard deviation. I just updated the python file on GitHub
